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Computer Science Principles
  • Introduction
  • Overview
  • Course at a Glance
  • Course Exam Description
  • Create Performance Task
  • Reference Sheet
  • Resources
  • Big Idea 1
    • 1.1 Collaboration
    • 1.2 Program Function and Purpose
    • 1.3 Program Design and Development
    • 1.4 Identifying and Correcting Errors
  • Big Idea 2
    • 2.1 Binary Numbers
    • 2.2 Data Compression
    • 2.3 Extracting Information from Data
    • 2.4 Using Programs with Data
  • Big Idea 3
    • 3.1 Variables and Assignments
    • 3.2 Data Abstraction
    • 3.3 Mathematical Expressions
    • 3.4 Strings
    • 3.5 Boolean Expression
    • 3.6 Conditionals
    • 3.7 Nested Conditionals
    • 3.8 Iteration
    • 3.9 Developing Algorithms
    • 3.10 Lists
    • 3.11 Binary Search
    • 3.12 Calling Procedures
    • 3.13 Developing Procedures
    • 3.14 Libraries
    • 3.15 Random Values
    • 3.16 Simulations
    • 3.17 Algorithmic Efficiency
    • 3.18 Undecidable Problems
  • Big Idea 4
    • 4.1 The Internet
    • 4.2 Fault Tolerant
    • 4.3 Parallel and Distributed Computing
  • Big Idea 5
    • 5.1 Beneficial and Harmful Effects
    • 5.2 Digital Divide
    • 5.3 Computing Bias
    • 5.4 Crowdsourcing
    • 5.5 Legal and Ethical Concerns
    • 5.6 Safe Computing
  • Code
    • Week 10
    • Week 11
    • Week 12
    • Week 13
    • Week 14
    • Week 15
    • Week 16
    • Week 17
    • Week 18
    • Week 19
    • Week 20
    • Week 21
    • Week 22
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  • Enduring Understanding
  • Learning Objective
  • Essential Knowledge

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  1. Big Idea 5

5.3 Computing Bias

Enduring Understanding

While computing innovations are typically designed to achieve a specific purpose, they may have unintended consequences.

Learning Objective

Explain how bias exists in computing innovations.

Essential Knowledge

Computing innovations can reflect existing human biases because of biases written into the algorithms or biases in the data used by the innovation.

Programmers should take action to reduce bias in algorithms used for computing innovations as a way of combating existing human biases.

Biases can be embedded at all levels of software development.

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Last updated 1 year ago

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